Data & Knowledge Management

Starting from my data analysis skills, I was entrusted with leading a team responsible for data management and its utilization to support evidence-based conservation.

Furthermore, the team I led underwent further development and was tasked with knowledge management within the department.

As part of an organization, there are certain aspects that cannot be shared publicly. However, here are some examples of my work accomplishments:

Data Management

I am confident that adopting a data-driven approach within the organization’s operations will result in rapid growth, as all decisions are consistently made by relying on data.

We initiate the data management process by defining and elaborating on key performance indicators in the Country Strategy and several key activities that also reflect the organization’s vision and mission. The outcomes of this process are subsequently used to construct data models and data sources as the basis for data collection in the field.

Our colleagues in the field collect data through their respective activities. We employ tools such as the Spatial Monitoring and Reporting Tool (SMART) and camera traps to record data in various formats such as tables, photographs, GPX files, and other data types. All of this data is accumulated in a centralized cloud-based data repository, organized in a structured manner using appropriate data models and schemas. Meanwhile, our activity reports are inputted into a document repository within the knowledge management system.

A layered process of data cleaning and data quality assessment is carried out to ensure accuracy, completeness, and reliability. This process begins with the data operators in the landscape and extends to the central level. It includes cleansing and preprocessing the data to eliminate errors, inconsistencies, duplicates, and irrelevant information. We develop quality metrics and processes to identify and resolve data issues. Data that successfully passes through this process is then inputted into SQL databases to facilitate data extraction by data analysts.

To generate reports and visualizations that effectively communicate findings, we construct a near-real-time information system build on R and RShiny based on several key performance indicators.

Through the establishment of data policies and standard operating procedures (SOPs), we determine access controls and permissions to ensure appropriate data access for different users or groups, including data sharing policies. This entails defining roles and responsibilities, data stewardship, data retention, and archiving strategies. We perform monthly backups to ensure the security of our data.

Knowledge Management

Aiming to be an evidence-based organization, our unit helps organization make the best use of knowledge and information by making it easy to find, share, and use.

By utilizing Microsoft SharePoint as the main platform, we store and manage knowledge products such as reports and publications in the form of scientific papers, books, booklets, and popular articles, making them easily discoverable and accessible to all staff.

In addition to being presented as documents, standard operating procedures (SOPs) are also condensed into shorter and more easily readable and understandable articles in the “how-to” and “frequently asked questions” formats, particularly for field teams. These articles are managed in a knowledge base with search features based on keywords and tags to ensure that staff can quickly find the information they are looking for.

Tacit knowledge, especially in the form of lessons learned, such as best practices in carrying out conservation activities and the field staff’s years of experience, also be included in the knowledge base.